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Machine Learning Manager Jobs in Maine (NOW HIRING)

Data Scientist

Portland, ME ยท On-site

$87K - $123K/yr

Hands-on experience with classical machine learning methods such as linear/logistic regression ... Ability to manage assigned tasks, meet deadlines, and maintain high-quality work. * Proactive ...

Sr AI Product Manager

Portland, ME ยท On-site

$155K - $175K/yr

Strong understanding of machine learning, LLMs, and modern AI architectures. Hands-on experience ... Strong stakeholder management in cross-functional environments Preferred (Nice to Have)

Sr AI Product Manager

Portland, ME ยท On-site

$155K - $175K/yr

Strong understanding of machine learning, LLMs, and modern AI architectures. Hands-on experience ... Strong stakeholder management in cross-functional environments Preferred (Nice to Have)

Product Manager Department: Product Reports To: Phillip Greer, CEO Work Location: Remote in the ... Research and recommend emerging technologies (e.g., AI, machine learning, generative content tools ...

$117K - $154K/yr

Manage and optimize the performance of relational databases, ensuring data availability ... pipelines and machine learning models. o Understanding of Generative AI and Deep Learning ...

Advance AI tooling initiatives by providing QA for machine learning and normalization model outputs ... Proven ability to work independently, manage competing priorities, and deliver in a fast-paced ...

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Showing results 1-20

Machine Learning Manager information

See Maine salary details

$49.4K

$79.1K

$114.2K

How much do machine learning manager jobs pay per year?

As of Jun 7, 2026, the average yearly pay for machine learning manager in Maine is $79,110.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,900.00 and $89,600.00 per year, depending on experience, location, and employer.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Maine? The most popular types of Machine Learning jobs in Maine are:
What are popular job titles related to Machine Learning Manager jobs in Maine? For Machine Learning Manager jobs in Maine, the most frequently searched job titles are:
What job categories do people searching Machine Learning Manager jobs in Maine look for? The top searched job categories for Machine Learning Manager jobs in Maine are:
What cities in Maine are hiring for Machine Learning Manager jobs? Cities in Maine with the most Machine Learning Manager job openings:
Infographic showing various Machine Learning Manager job openings in Maine as of May 2026, with employment types broken down into 3% As Needed, 38% Full Time, 56% Part Time, and 3% Temporary. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $79,110 per year, or $38 per hour.

Data Scientist

Northeastern University

Portland, ME โ€ข On-site

$87K - $123K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago


Job description

About the Opportunity
JOB SUMMARY
This is a full-time, one-year term appointment with the possibility of renewal. The position is in-person at Northeastern's Roux Institute in Portland, Maine.
The Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University's Experiential AI Institute, will support the development and delivery of AI and data science solutions across diverse industries. The role is designed for early-career data scientists who will work under the guidance of senior data scientists, AI engineers, and faculty leads.
The Data Scientist will contribute to data analysis, feature engineering, model development, evaluation, and documentation, while progressively gaining exposure to production systems, client-facing work, and modern AI practices across Predictive AI and Generative AI use cases.
Education & Experience
  • Master's degree (required) or Ph.D. (optional) in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely related field.
  • 0-2 years of industry, research, or applied project experience in data science or machine learning.
  • Experience gained through internships, co-ops, academic research, or applied capstone projects is acceptable.
  • Industry experience is preferred.

Knowledge, Skills, and Abilities
Technical and Analytical Foundations
  • Solid understanding of statistical methods, regression, hypothesis testing, and basic experimental design.
  • Hands-on experience with classical machine learning methods such as linear/logistic regression, decision trees, and gradient boosting.
  • Familiarity with deep learning concepts and modern architectures (e.g., convolutional neural networks or transformers); deep specialization is not required.
  • Exposure to Generative AI concepts and large language models (LLMs) is a plus.
  • Proficiency in Python for data analysis and model development (NumPy, pandas, scikit-learn).
  • Working knowledge of SQL and relational databases.
  • Familiarity with at least one ML or deep learning framework (e.g., PyTorch, TensorFlow, HuggingFace).
Model Development and Delivery Support
  • Perform data cleaning, exploratory data analysis (EDA), and feature engineering.
  • Train, evaluate, and compare machine learning models under supervision.
  • Assist with model validation, performance monitoring, and documentation.
  • Contribute to ML pipelines and collaborate with ML engineers on deployment-related tasks.
Collaboration and Communication
  • Ability to clearly communicate analytical findings to technical and non-technical audiences with guidance.
  • Collaborate effectively with cross-functional teams including data scientists, engineers, project managers, and faculty experts.
  • Willingness to participate in client meetings in a supporting role.
Preferred Experience
  • Exposure to NLP, computer vision, or speech processing through coursework or academic/industry projects.
  • Familiarity with cloud platforms (AWS, Azure, or GCP).
  • Understanding of software development best practices such as version control (Git) and Agile workflows.

Values & Professional Attributes
Ethical and Responsible AI
  • Awareness of ethical AI principles including fairness, transparency, and responsible model use.
  • Willingness to follow established governance, documentation, and review practices.
Learning and Growth Mindset
  • Strong curiosity and motivation to learn new tools, techniques, and AI methods.
  • Openness to feedback and mentorship.
Execution and Ownership
  • Ability to manage assigned tasks, meet deadlines, and maintain high-quality work.
  • Proactive attitude and willingness to take increasing responsibility over time.

Position Type
Research
Additional Information
Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.
Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.
All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.
Compensation Grade/Pay Type:
111S
Expected Hiring Range:
$87,785.00 - $123,998.75
With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.